Determination of suitable areas for the solar power plant (SPW) and swot analysis in the araban district of Gaziantep by GIS and remote sensing methodology
2020
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Advisor: Doç. Dr. Erdihan Tunç
Abstract (EN)
Many ecological problems occur during the use of consumable energy sources. Recently, due to excessive increase prices of fossil fuel resources, renewable energy sources are encouraged in Turkey and in the World. One of these sources is Solar Power Plants (SPW). It is an important issue to determine the places where SPWs will be established in a correct and planned way. In order to ensure the conformity of SPWs, the places where the sunshine duration is high, do not not harm the ecological diversity and do not narrow the 1st class agricultural lands need to be determined. In this study, it is aimed to determine the suitable areas with respect to the both ecological and high energy efficiency and economic context in Araban District. Sunshine duration is relatively hight but the climatic suitability of Araban for SPW has not been evaluated. In this study, by using GIS, parameters are determined by multi-criteria decision-making method and place conformity analysis is performed. Along with the present study, various layers were formed for SPW area compatibility using GIS and remote sensing methods. These are lithology, land surface temperature (LST), land use capability classes, land use map, vegetation map, slope, elevation and elevation maps. The results of the study show that there are suitable areas for the establishment of SPW areas in Araban District. These areas are the agriculturally inefficient basalt surfaces facing the southern slope, which lacks a slightly sloping vegetation. The SPW areas to be established in these areas will not only create ecological damage but also will be economically profitable with high energy efficiency.
Author
Sevil Çelik
How to Cite
Sevil Çelik (Master Thesis). Determination of suitable areas for the solar power plant (SPW) and swot analysis in the araban district of Gaziantep by GIS and remote sensing methodology, 2020, Gaziantep University.
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